Summary Interest in metabolism and the vascular microenvironment continues to grow in a broad range of disciplines including neuroscience, cardiovascular biology, and the field of cancer research. Given their clinical importance, there are surprisingly few techniques available that can provide a systems-level view of these hallmarks together in vivo. Though there are many bench-top microscopes and metabolic tools available to provide exquisite resolution and contrast for metabolic or vascular imaging, they often require researchers to transport animals to specialized facilities and this limits access for high frequency imaging, these systems require extensive training and often have fields of view (FOV), resolution and wavelengths that fits only the most common use cases (in the case of optical microscopy systems). Our goals are to develop and validate a point-of-investigation metabolic and vascular imaging system and corresponding algorithms that will democratize access to imaging for cancer research in individual cancer pharmacology labs. The capabilities of our system will be demonstrated through imaging of metabolism, vascular function, and architecture at a spatial resolution that can visualize proliferative, regressive, residual, and recurrent disease in a breast cancer model. Our technique could provide a comprehensive understanding how the metabolic characteristics of tumors impact therapeutic outcome and can be used in a wide range of cancer pharmacology applications to improve the effectiveness of cancer therapy. The specific goals of this proposal are to develop an low-cost, portable, user friendly, CapCell scope to image key metabolic and vascular endpoints simultaneously with a wide range of FOVs and resolutions (Aim 1), demonstrate that this technology provides comparable information and can complement established methods in well-established murine tumor models of breast cancer (Aim 2), and validate the technology on GEM model derived mammospheres and in vivo mammary window models of GEM model derived tumors (Aim 3). This proposal sets the foundation for translating our technology to patient-derived xenograft (PDX) models and patient-derived organoids, which have been shown to be able to faithfully recapitulate many of the micro-environmental features of patient tumors, allowing us move our technique forward towards translational pharmaceutical research.